Transcriptomes of human whole blood cells in sepsis patients
RNA-seq (gene expression) · human · 40 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 40 samples: 30 × sepsis patient vs 10 × healthy controlGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Construction of a robust sepsis prognostic classifier based on E3 ubiquitin ligase-related genesFrontiers in molecular biosciences · 2026
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE294985_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1252151 and SRA study SRP579501. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 30 samples read as cases, 10 as controls.
How we read this: 2 replicated groups read from 40 sample titles; they account for 40 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8936490 healthy control 1 healthy control
- GSM8936491 healthy control 2 healthy control
- GSM8936492 healthy control 3 healthy control
- GSM8936493 healthy control 4 healthy control
- GSM8936494 healthy control 5 healthy control
- GSM8936495 healthy control 6 healthy control
- GSM8936496 healthy control 7 healthy control
- GSM8936497 healthy control 8 healthy control
- GSM8936498 healthy control 9 healthy control
- GSM8936499 healthy control 10 healthy control
- GSM8936500 sepsis patient 1 sepsis patient
- GSM8936501 sepsis patient 2 sepsis patient
- GSM8936502 sepsis patient 3 sepsis patient
- GSM8936503 sepsis patient 4 sepsis patient
- GSM8936504 sepsis patient 5 sepsis patient
- GSM8936505 sepsis patient 6 sepsis patient
- GSM8936506 sepsis patient 7 sepsis patient
- GSM8936507 sepsis patient 8 sepsis patient
- GSM8936508 sepsis patient 9 sepsis patient
- GSM8936509 sepsis patient 10 sepsis patient
- GSM8936510 sepsis patient 11 sepsis patient
- GSM8936511 sepsis patient 12 sepsis patient
- GSM8936512 sepsis patient 13 sepsis patient
- GSM8936513 sepsis patient 14 sepsis patient
- GSM8936514 sepsis patient 15 sepsis patient
- GSM8936515 sepsis patient 16 sepsis patient
- GSM8936516 sepsis patient 17 sepsis patient
- GSM8936517 sepsis patient 18 sepsis patient
- GSM8936518 sepsis patient 19 sepsis patient
- GSM8936519 sepsis patient 20 sepsis patient
- GSM8936520 sepsis patient 21 sepsis patient
- GSM8936521 sepsis patient 22 sepsis patient
- GSM8936522 sepsis patient 23 sepsis patient
- GSM8936523 sepsis patient 24 sepsis patient
- GSM8936524 sepsis patient 25 sepsis patient
- GSM8936525 sepsis patient 26 sepsis patient
- GSM8936526 sepsis patient 27 sepsis patient
- GSM8936527 sepsis patient 28 sepsis patient
- GSM8936528 sepsis patient 29 sepsis patient
- GSM8936529 sepsis patient 30 sepsis patient
- GSE243219 Comparative Analysis of Host Responses Between Sepsis and COVID-19: A Prospective Observational Study of Whole Blood Transcriptome 144 samples shares sepsis, whole, blood
- GSE205672 Transcriptomes of human PBMCs and monocytes in sepsis patients 460 samples shares transcriptomes, sepsis
- GSE330188 Crnic Institute Human Trisome Project - Tofacitinib for Immune Skin Conditions in Down Syndrome: PolyA RNAseq from whole blood 194 samples shares whole, blood
- GSE267625 Whole blood transcriptome in long-COVID patients reveals association with lung function and immune response 111 samples shares whole, blood
- GSE265753 Single cell gene expression profile of peripheral whole blood cells from long COVID patients 13 samples shares whole, blood
- GSE288704 Whole transcriptome analysis of unmutated sporadic ALS patients’ peripheral blood reveals phenotype-specific gene expression signature 66 samples shares whole, blood
- GSE288604 Whole blood transcriptomics characterize molecular phenotypes of pulmonary Mycobacterium avium complex disease 200 samples shares whole, blood
- GSE215274 Identification of Whole Blood Gene Expression Signature to Predict the Therapeutic Effect of Nintedanib in Idiopathic Pulmonary Fibrosis 177 samples shares whole, blood
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.